Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add commands/ashfaqbs/software-dev-ai-claude-toolkit/code-reviewgit clone --depth 1 https://github.com/Ashfaqbs/software-dev-ai-claude-toolkitWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00010 | $0.00328 |
| Opus 5 | $0.00005 | $0.00164 |
| Sonnet 5 | $0.00002 | $0.00066 |
| Haiku 4.5 | $0.00001 | $0.00033 |
Grade A, and why
code-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Code Review
Review all uncommitted changes in this project.
Process
- Run
git diffto see all staged and unstaged changes. - Run
git diff --cachedto see staged changes specifically.
Check For
Security
- Hardcoded secrets, API keys, passwords, tokens
- SQL injection (raw queries without parameterization)
- Missing input validation on user-facing endpoints
- Sensitive data in logs
- Missing auth/authorization checks
Code Quality
- Functions longer than 50 lines
- Deep nesting (> 3 levels)
- Mutable shared state
- Missing error handling
- Copy-pasted / duplicated logic
- Dead code or unused imports
Testing
- Are new code paths covered by tests?
- Are edge cases tested?
Stack-Specific
- Java: proper use of Optional, records, @Transactional scope, resource cleanup
- Python: type hints present, async/sync consistency, Pydantic models for I/O
- JS: no
var, noany, noconsole.log, proper error boundaries in React
Output
Provide a summary with severity levels:
- CRITICAL: Must fix before merge (security, data loss)
- WARNING: Should fix (code quality, performance)
- SUGGESTION: Nice to have (style, readability)
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 46 lines · 10 tokens per session scan A 2ed450f04dd3
code-review is a command published in the GitHub repository Ashfaqbs/software-dev-ai-claude-toolkit (24 stars, last pushed 6mo ago), licensed MIT. It adds 10 tokens to every session and 328 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
constitution
Create or update the project constitution from interactive or provided principle inputs.